We, in the Lee Laboratory in the Sergievsky Center & Taub Institute at the Columbia University Irving Medical Center in New York City, are seeking individual with formal training in bioinformatics, data science, statistical genetics, or genetic epidemiology. This bioinformatics analyst position is immediately available to work on an NIH-funded multi-center project on Biomarkers of Alzheimer's Disease (AD) in Down Syndrome. This project will generate genomic, transcriptomic, proteomic, metabolomic, imaging (MRI and PET), neuropsychological data, and AD status. Using rich, high dimensional data, the candidate will be engaged in research to identify and characterize genetic contributions as well as pathways toward cognitive decline, Alzheimer's disease, and other age-related neurodegenerative diseases in this high-risk population. The candidate will also collaborate with other team members who work on gene mapping and functional genetics of Alzheimer's Disease in PSEN1 carrier families and those who work on the genetics of healthy aging. In addition, the candidate will work with faculty members with a wide range of expertise (e.g., statistical genetics, epidemiology, neurology, bioinformatics, statistics, cell biology, etc.) and other team members on gene mapping, functional genetic and translational studies.
Responsible for assembling, executing, and developing the latest bioinformatics pipelines for QA/QC and analysis of omics data.
Contribute to the develop bioinformatics and analysis workflows to answer targeted questions about molecular profiles of AD and related phenotypes.
Use bioinformatics tools to analyze high-throughput omics datasets, including whole genome/exome sequencing, GWAS, and RNA-seq data
Develop and implement methods for integrative analysis of available multi-omics datasets, including genomics, transcriptomics, proteomics and metabolomics
Perform analyses to examine how above multi-omics data are associated with neuropsychological and medical data.
Perform statistical analysis of the genomic data in family-based as well as case-control or cohort study designs.
Produce subsets of data for distribution to collaborators and/or data repositories as approved by the principal investigators.
Prepare manuscripts, grant proposals, and presentations for scientific meetings
Work independently and collaboratively with a highly interactive research group
A Master's Degree in computational biology, bioinformatics, biostatistics/statistics, genetic epidemiology, or other relevant computational disciplines with several years of relevant experience in this field
Proficient in shell scripting and programming proficiency in R, Python, C, C++, or Java on UNIX/Linux environments, particularly with large data files in various formats
Experience in analysis of human sequence data using bioinformatics tools (e.g., SAMtools, GATK, Picard, STAR, RSEM) and omics databases (Ensembl, 1000 Genomes, GnomAD, GTex, HapMap, ENCODE, etc.)
Working knowledge of statistical genetics will be a plus
Ability to analyze data on the cloud (e.g., AWS, Google or Azure) will be a plus
Excellent written and verbal communication
Qualified candidates should e-mail a cover letter, curriculum vitae, and list of three references to Dr. Joseph Lee at JHL2@cumc.columbia.edu (cc: email@example.com) with
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